يعرض 141 - 152 نتائج من 152 نتيجة بحث عن 'algorithm flow function', وقت الاستعلام: 0.12s تنقيح النتائج
  1. 141

    Relational network prepared by the authoring team. حسب Lesedi Mamodise Modise (20826978)

    منشور في 2025
    "…The visualization was rendered using React Flow (a node-based graph visualization library), and the layout algorithm was implemented with the support of D3.js (a toolkit for data-driven documents). …"
  2. 142

    HVTN 705 data repo: Unbiased cell clustering analysis of vaccine-induced T cell responses in the Imbokodo HIV-1 vaccine trial حسب Valentin Voillet (19201102)

    منشور في 2025
    "…Traditional methods for analysing these responses might be biased towards specific functionalities or epitopes. This study presents an unsupervised and unbiased clustering analysis workflow, using the Leiden algorithm followed by selection of antigen-specific clusters using MIMOSA positivity calls, for high-dimensional flow cytometry data to identify distinct T cell populations associated with protection in the HVTN 705/HPX2008/Imbokodo HIV-1 vaccine efficacy trial.…"
  3. 143

    Table 1_Demethylase FTO mediates m6A modification of ENST00000619282 to promote apoptosis escape in rheumatoid arthritis and the intervention effect of Xinfeng Capsule.docx حسب Fanfan Wang (1669474)

    منشور في 2025
    "…</p>Methods<p>A retrospective analysis was conducted on 1603 RA patients using association rule mining and random walk algorithms to evaluate the efficacy of XFC. The proliferation and apoptosis of co-cultured RA-FLS were assessed using CCK-8, flow cytometry (FCM), and molecular biology techniques. …"
  4. 144

    <b>NanoNeuroBot: Beyond Healing, Toward Human Connection</b> حسب ahmed hossam (21420446)

    منشور في 2025
    "…It uses a flexible electrode array, EMG signal sensors, and a smart AI app (built on TensorFlow and Flutter) to optimize stimulation patterns. …"
  5. 145

    Table 1_Machine learning integration with multi-omics data constructs a robust prognostic model and identifies PTGES3 as a therapeutic target for precision oncology in lung adenoca... حسب Lian-jie Ruan (22327876)

    منشور في 2025
    "…PTGES3 expression was evaluated via tissue microarray immunohistochemistry. Functional assays (CCK-8, colony formation, flow cytometry, Western blot) after lentiviral knockdown in lung cancer cells assessed its effects on proliferation, apoptosis, and cell cycle. …"
  6. 146

    Data Sheet 1_Machine learning integration with multi-omics data constructs a robust prognostic model and identifies PTGES3 as a therapeutic target for precision oncology in lung ad... حسب Lian-jie Ruan (22327876)

    منشور في 2025
    "…PTGES3 expression was evaluated via tissue microarray immunohistochemistry. Functional assays (CCK-8, colony formation, flow cytometry, Western blot) after lentiviral knockdown in lung cancer cells assessed its effects on proliferation, apoptosis, and cell cycle. …"
  7. 147

    Navigating complex care pathways–healthcare workers’ perspectives on health system barriers for children with tuberculous meningitis in Cape Town, South Africa حسب Dzunisani Patience Baloyi (19452687)

    منشور في 2025
    "…An integrated data system and alert functions could flag multiple healthcare visits and improve communication between different healthcare facilities during diagnosis and treatment. …"
  8. 148

    Table 1_Identification of novel molecular subtypes and construction of a prognostic signature via multi-omics analysis and machine learning in lung adenocarcinoma.xlsx حسب Ke Ma (260231)

    منشور في 2025
    "…</p>Results<p>Our analysis revealed that the novel molecular subtypes exhibited differences in prognoses, biological functions, and immune infiltration profiles in LUAD. …"
  9. 149

    Presentation 1_Identification of novel molecular subtypes and construction of a prognostic signature via multi-omics analysis and machine learning in lung adenocarcinoma.zip حسب Ke Ma (260231)

    منشور في 2025
    "…</p>Results<p>Our analysis revealed that the novel molecular subtypes exhibited differences in prognoses, biological functions, and immune infiltration profiles in LUAD. …"
  10. 150

    Data Sheet 1_Identification of novel molecular subtypes and construction of a prognostic signature via multi-omics analysis and machine learning in lung adenocarcinoma.docx حسب Ke Ma (260231)

    منشور في 2025
    "…</p>Results<p>Our analysis revealed that the novel molecular subtypes exhibited differences in prognoses, biological functions, and immune infiltration profiles in LUAD. …"
  11. 151

    Data Sheet 1_Resveratrol contributes to NK cell-mediated breast cancer cytotoxicity by upregulating ULBP2 through miR-17-5p downmodulation and activation of MINK1/JNK/c-Jun signali... حسب Bisha Ding (5803799)

    منشور في 2025
    "…</p>Methods<p>The effects of RES on ULBP2 expression were detected with qRT-PCR, western blot, flow cytometry analysis and immunohistochemistry. …"
  12. 152

    An Ecological Benchmark of Photo Editing Software: A Comparative Analysis of Local vs. Cloud Workflows حسب Pierre-Alexis DELAROCHE (22092572)

    منشور في 2025
    "…Performance Profiling Algorithms Energy Measurement Methodology # Pseudo-algorithmic representation of measurement protocol def capture_energy_metrics(workflow_type: WorkflowEnum, asset_vector: List[PhotoAsset]) -> EnergyProfile: baseline_power = sample_idle_power_draw(duration=30) with PowerMonitoringContext() as pmc: start_timestamp = rdtsc() # Read time-stamp counter if workflow_type == WorkflowEnum.LOCAL: result = execute_local_pipeline(asset_vector) elif workflow_type == WorkflowEnum.CLOUD: result = execute_cloud_pipeline(asset_vector) end_timestamp = rdtsc() energy_profile = EnergyProfile( duration=cycles_to_seconds(end_timestamp - start_timestamp), peak_power=pmc.get_peak_consumption(), average_power=pmc.get_mean_consumption(), total_energy=integrate_power_curve(pmc.get_power_trace()) ) return energy_profile Statistical Analysis Framework Our analytical pipeline employs advanced statistical methodologies including: Variance Decomposition: ANOVA with nested factors for hardware configuration effects Regression Analysis: Generalized Linear Models (GLM) with log-link functions for energy modeling Temporal Analysis: Fourier transform-based frequency domain analysis of power consumption patterns Cluster Analysis: K-means clustering with Euclidean distance metrics for workflow classification Data Validation and Quality Assurance Measurement Uncertainty Quantification All energy measurements incorporate systematic and random error propagation analysis: Instrument Precision: ±0.1W for CPU power, ±0.5W for GPU power Temporal Resolution: 1ms sampling with Nyquist frequency considerations Calibration Protocol: NIST-traceable power standards with periodic recalibration Environmental Controls: Temperature-compensated measurements in climate-controlled facility Outlier Detection Algorithms Statistical outliers are identified using the Interquartile Range (IQR) method with Tukey's fence criteria (Q₁ - 1.5×IQR, Q₃ + 1.5×IQR). …"